Overview

Brought to you by YData

Dataset statistics

Number of variables15
Number of observations9357
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 MiB
Average record size in memory234.5 B

Variable types

DateTime2
Numeric13

Alerts

AH is highly overall correlated with PT08.S4(NO2) and 1 other fieldsHigh correlation
C6H6(GT) is highly overall correlated with CO(GT) and 5 other fieldsHigh correlation
CO(GT) is highly overall correlated with C6H6(GT) and 6 other fieldsHigh correlation
NO2(GT) is highly overall correlated with CO(GT) and 2 other fieldsHigh correlation
NOx(GT) is highly overall correlated with CO(GT) and 4 other fieldsHigh correlation
PT08.S1(CO) is highly overall correlated with C6H6(GT) and 6 other fieldsHigh correlation
PT08.S2(NMHC) is highly overall correlated with C6H6(GT) and 5 other fieldsHigh correlation
PT08.S3(NOx) is highly overall correlated with C6H6(GT) and 6 other fieldsHigh correlation
PT08.S4(NO2) is highly overall correlated with AH and 5 other fieldsHigh correlation
PT08.S5(O3) is highly overall correlated with C6H6(GT) and 6 other fieldsHigh correlation
T is highly overall correlated with AH and 1 other fieldsHigh correlation

Reproduction

Analysis started2025-05-21 16:10:51.187235
Analysis finished2025-05-21 16:11:32.592073
Duration41.4 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Date
Date

Distinct391
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size73.2 KiB
Minimum2004-03-10 00:00:00
Maximum2005-04-04 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-21T21:41:32.752169image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:32.957041image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Time
Date

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size73.2 KiB
Minimum2025-05-21 00:00:00
Maximum2025-05-21 23:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-21T21:41:33.138911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:33.358972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

CO(GT)
Real number (ℝ)

High correlation 

Distinct97
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-34.207524
Minimum-200
Maximum11.9
Zeros0
Zeros (%)0.0%
Negative1683
Negative (%)18.0%
Memory size73.2 KiB
2025-05-21T21:41:33.564963image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile-200
Q10.6
median1.5
Q32.6
95-th percentile4.7
Maximum11.9
Range211.9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation77.65717
Coefficient of variation (CV)-2.2701781
Kurtosis0.77830552
Mean-34.207524
Median Absolute Deviation (MAD)1
Skewness-1.6661795
Sum-320079.8
Variance6030.6361
MonotonicityNot monotonic
2025-05-21T21:41:33.810300image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 1683
 
18.0%
1 305
 
3.3%
1.4 279
 
3.0%
1.6 275
 
2.9%
1.5 273
 
2.9%
1.1 262
 
2.8%
0.7 260
 
2.8%
1.7 258
 
2.8%
1.3 253
 
2.7%
0.8 251
 
2.7%
Other values (87) 5258
56.2%
ValueCountFrequency (%)
-200 1683
18.0%
0.1 33
 
0.4%
0.2 45
 
0.5%
0.3 98
 
1.0%
0.4 160
 
1.7%
0.5 217
 
2.3%
0.6 244
 
2.6%
0.7 260
 
2.8%
0.8 251
 
2.7%
0.9 248
 
2.7%
ValueCountFrequency (%)
11.9 1
< 0.1%
11.5 1
< 0.1%
10.2 2
< 0.1%
10.1 1
< 0.1%
9.9 1
< 0.1%
9.5 1
< 0.1%
9.4 1
< 0.1%
9.3 1
< 0.1%
9.2 1
< 0.1%
9.1 2
< 0.1%

PT08.S1(CO)
Real number (ℝ)

High correlation 

Distinct1042
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1048.9901
Minimum-200
Maximum2040
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-05-21T21:41:34.057099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile746
Q1921
median1053
Q31221
95-th percentile1502
Maximum2040
Range2240
Interquartile range (IQR)300

Descriptive statistics

Standard deviation329.83271
Coefficient of variation (CV)0.31442882
Kurtosis5.8369357
Mean1048.9901
Median Absolute Deviation (MAD)147
Skewness-1.7215034
Sum9815400
Variance108789.62
MonotonicityNot monotonic
2025-05-21T21:41:34.253808image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
973 30
 
0.3%
1100 28
 
0.3%
988 26
 
0.3%
969 26
 
0.3%
925 26
 
0.3%
938 26
 
0.3%
966 25
 
0.3%
970 25
 
0.3%
984 25
 
0.3%
Other values (1032) 8754
93.6%
ValueCountFrequency (%)
-200 366
3.9%
647 1
 
< 0.1%
649 1
 
< 0.1%
655 1
 
< 0.1%
667 3
 
< 0.1%
669 1
 
< 0.1%
676 1
 
< 0.1%
678 1
 
< 0.1%
679 1
 
< 0.1%
681 1
 
< 0.1%
ValueCountFrequency (%)
2040 1
< 0.1%
2008 1
< 0.1%
1982 1
< 0.1%
1975 1
< 0.1%
1973 1
< 0.1%
1961 1
< 0.1%
1956 1
< 0.1%
1934 1
< 0.1%
1918 1
< 0.1%
1917 1
< 0.1%

NMHC(GT)
Real number (ℝ)

Distinct430
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-159.09009
Minimum-200
Maximum1189
Zeros0
Zeros (%)0.0%
Negative8443
Negative (%)90.2%
Memory size73.2 KiB
2025-05-21T21:41:34.481043image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile-200
Q1-200
median-200
Q3-200
95-th percentile144.2
Maximum1189
Range1389
Interquartile range (IQR)0

Descriptive statistics

Standard deviation139.78909
Coefficient of variation (CV)-0.87867881
Kurtosis18.863824
Mean-159.09009
Median Absolute Deviation (MAD)0
Skewness4.0757845
Sum-1488606
Variance19540.99
MonotonicityNot monotonic
2025-05-21T21:41:34.956816image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 8443
90.2%
66 14
 
0.1%
40 9
 
0.1%
29 9
 
0.1%
88 8
 
0.1%
93 8
 
0.1%
84 7
 
0.1%
55 7
 
0.1%
95 7
 
0.1%
60 7
 
0.1%
Other values (420) 838
 
9.0%
ValueCountFrequency (%)
-200 8443
90.2%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
14 2
 
< 0.1%
16 1
 
< 0.1%
17 4
 
< 0.1%
18 2
 
< 0.1%
ValueCountFrequency (%)
1189 1
< 0.1%
1129 1
< 0.1%
1084 1
< 0.1%
1042 1
< 0.1%
974 1
< 0.1%
926 1
< 0.1%
899 1
< 0.1%
880 1
< 0.1%
872 1
< 0.1%
840 1
< 0.1%

C6H6(GT)
Real number (ℝ)

High correlation 

Distinct408
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8656834
Minimum-200
Maximum63.7
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-05-21T21:41:35.157000image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile0.7
Q14
median7.9
Q313.6
95-th percentile24.42
Maximum63.7
Range263.7
Interquartile range (IQR)9.6

Descriptive statistics

Standard deviation41.380206
Coefficient of variation (CV)22.17965
Kurtosis19.188651
Mean1.8656834
Median Absolute Deviation (MAD)4.5
Skewness-4.5087629
Sum17457.2
Variance1712.3215
MonotonicityNot monotonic
2025-05-21T21:41:35.406803image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
3.6 84
 
0.9%
2.8 82
 
0.9%
3.8 79
 
0.8%
4 78
 
0.8%
3.1 77
 
0.8%
3 76
 
0.8%
2.5 75
 
0.8%
2.9 73
 
0.8%
5.4 72
 
0.8%
Other values (398) 8295
88.7%
ValueCountFrequency (%)
-200 366
3.9%
0.1 2
 
< 0.1%
0.2 8
 
0.1%
0.3 10
 
0.1%
0.4 14
 
0.1%
0.5 20
 
0.2%
0.6 23
 
0.2%
0.7 31
 
0.3%
0.8 25
 
0.3%
0.9 25
 
0.3%
ValueCountFrequency (%)
63.7 1
< 0.1%
52.1 1
< 0.1%
50.8 1
< 0.1%
50.7 1
< 0.1%
50.6 1
< 0.1%
49.5 1
< 0.1%
49.4 1
< 0.1%
48.2 1
< 0.1%
47.7 1
< 0.1%
47.5 1
< 0.1%

PT08.S2(NMHC)
Real number (ℝ)

High correlation 

Distinct1246
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean894.59528
Minimum-200
Maximum2214
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-05-21T21:41:35.632575image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile471
Q1711
median895
Q31105
95-th percentile1415
Maximum2214
Range2414
Interquartile range (IQR)394

Descriptive statistics

Standard deviation342.33325
Coefficient of variation (CV)0.3826683
Kurtosis2.3700888
Mean894.59528
Median Absolute Deviation (MAD)195
Skewness-0.79343464
Sum8370728
Variance117192.06
MonotonicityNot monotonic
2025-05-21T21:41:35.880873image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
853 25
 
0.3%
880 23
 
0.2%
800 23
 
0.2%
859 23
 
0.2%
985 22
 
0.2%
783 21
 
0.2%
769 21
 
0.2%
776 21
 
0.2%
850 21
 
0.2%
Other values (1236) 8791
94.0%
ValueCountFrequency (%)
-200 366
3.9%
383 2
 
< 0.1%
387 1
 
< 0.1%
388 1
 
< 0.1%
390 2
 
< 0.1%
397 1
 
< 0.1%
399 1
 
< 0.1%
402 2
 
< 0.1%
407 2
 
< 0.1%
408 1
 
< 0.1%
ValueCountFrequency (%)
2214 1
< 0.1%
2007 1
< 0.1%
1983 1
< 0.1%
1981 1
< 0.1%
1980 1
< 0.1%
1959 1
< 0.1%
1958 1
< 0.1%
1935 1
< 0.1%
1924 1
< 0.1%
1920 1
< 0.1%

NOx(GT)
Real number (ℝ)

High correlation 

Distinct926
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168.61697
Minimum-200
Maximum1479
Zeros0
Zeros (%)0.0%
Negative1639
Negative (%)17.5%
Memory size73.2 KiB
2025-05-21T21:41:36.134529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile-200
Q150
median141
Q3284
95-th percentile653.2
Maximum1479
Range1679
Interquartile range (IQR)234

Descriptive statistics

Standard deviation257.43387
Coefficient of variation (CV)1.5267376
Kurtosis1.5054171
Mean168.61697
Median Absolute Deviation (MAD)109
Skewness0.82523219
Sum1577749
Variance66272.196
MonotonicityNot monotonic
2025-05-21T21:41:36.472899image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 1639
 
17.5%
89 41
 
0.4%
65 37
 
0.4%
93 36
 
0.4%
122 36
 
0.4%
41 36
 
0.4%
132 35
 
0.4%
95 35
 
0.4%
180 35
 
0.4%
51 34
 
0.4%
Other values (916) 7393
79.0%
ValueCountFrequency (%)
-200 1639
17.5%
2 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 3
 
< 0.1%
11 4
 
< 0.1%
12 4
 
< 0.1%
ValueCountFrequency (%)
1479 1
< 0.1%
1389 2
< 0.1%
1369 1
< 0.1%
1358 1
< 0.1%
1345 1
< 0.1%
1310 1
< 0.1%
1301 1
< 0.1%
1290 1
< 0.1%
1253 1
< 0.1%
1247 1
< 0.1%

PT08.S3(NOx)
Real number (ℝ)

High correlation 

Distinct1222
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean794.99017
Minimum-200
Maximum2683
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-05-21T21:41:36.786726image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile410
Q1637
median794
Q3960
95-th percentile1281.2
Maximum2683
Range2883
Interquartile range (IQR)323

Descriptive statistics

Standard deviation321.99355
Coefficient of variation (CV)0.40502834
Kurtosis3.1048259
Mean794.99017
Median Absolute Deviation (MAD)161
Skewness-0.38475977
Sum7438723
Variance103679.85
MonotonicityNot monotonic
2025-05-21T21:41:36.967165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
767 25
 
0.3%
733 25
 
0.3%
846 25
 
0.3%
765 23
 
0.2%
876 23
 
0.2%
685 22
 
0.2%
816 22
 
0.2%
891 22
 
0.2%
830 22
 
0.2%
Other values (1212) 8782
93.9%
ValueCountFrequency (%)
-200 366
3.9%
322 1
 
< 0.1%
325 2
 
< 0.1%
328 1
 
< 0.1%
330 2
 
< 0.1%
334 1
 
< 0.1%
335 1
 
< 0.1%
340 2
 
< 0.1%
341 1
 
< 0.1%
345 1
 
< 0.1%
ValueCountFrequency (%)
2683 1
< 0.1%
2559 1
< 0.1%
2542 1
< 0.1%
2331 1
< 0.1%
2327 1
< 0.1%
2318 1
< 0.1%
2294 1
< 0.1%
2121 1
< 0.1%
2095 2
< 0.1%
2081 1
< 0.1%

NO2(GT)
Real number (ℝ)

High correlation 

Distinct284
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.148873
Minimum-200
Maximum340
Zeros0
Zeros (%)0.0%
Negative1642
Negative (%)17.5%
Memory size73.2 KiB
2025-05-21T21:41:37.159200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile-200
Q153
median96
Q3133
95-th percentile194
Maximum340
Range540
Interquartile range (IQR)80

Descriptive statistics

Standard deviation126.94046
Coefficient of variation (CV)2.1830252
Kurtosis0.27559907
Mean58.148873
Median Absolute Deviation (MAD)40
Skewness-1.2256296
Sum544099
Variance16113.879
MonotonicityNot monotonic
2025-05-21T21:41:37.336870image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 1642
 
17.5%
97 78
 
0.8%
117 77
 
0.8%
119 77
 
0.8%
95 75
 
0.8%
101 75
 
0.8%
114 75
 
0.8%
110 74
 
0.8%
115 73
 
0.8%
116 72
 
0.8%
Other values (274) 7039
75.2%
ValueCountFrequency (%)
-200 1642
17.5%
2 1
 
< 0.1%
3 1
 
< 0.1%
5 2
 
< 0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
11 2
 
< 0.1%
12 2
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
340 1
< 0.1%
333 1
< 0.1%
326 1
< 0.1%
322 1
< 0.1%
312 1
< 0.1%
310 1
< 0.1%
309 1
< 0.1%
306 1
< 0.1%
301 1
< 0.1%
296 1
< 0.1%

PT08.S4(NO2)
Real number (ℝ)

High correlation 

Distinct1604
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1391.4796
Minimum-200
Maximum2775
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-05-21T21:41:37.656758image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile757
Q11185
median1446
Q31662
95-th percentile2020.2
Maximum2775
Range2975
Interquartile range (IQR)477

Descriptive statistics

Standard deviation467.21012
Coefficient of variation (CV)0.33576497
Kurtosis3.2670279
Mean1391.4796
Median Absolute Deviation (MAD)236
Skewness-1.2441099
Sum13020075
Variance218285.3
MonotonicityNot monotonic
2025-05-21T21:41:37.896777image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
1488 24
 
0.3%
1580 22
 
0.2%
1539 21
 
0.2%
1467 20
 
0.2%
1638 19
 
0.2%
1490 18
 
0.2%
1418 18
 
0.2%
1321 17
 
0.2%
1511 17
 
0.2%
Other values (1594) 8815
94.2%
ValueCountFrequency (%)
-200 366
3.9%
551 1
 
< 0.1%
559 1
 
< 0.1%
561 1
 
< 0.1%
579 1
 
< 0.1%
601 1
 
< 0.1%
602 1
 
< 0.1%
605 1
 
< 0.1%
621 1
 
< 0.1%
637 1
 
< 0.1%
ValueCountFrequency (%)
2775 1
< 0.1%
2746 1
< 0.1%
2691 1
< 0.1%
2684 1
< 0.1%
2679 1
< 0.1%
2667 1
< 0.1%
2665 1
< 0.1%
2662 1
< 0.1%
2643 2
< 0.1%
2641 2
< 0.1%

PT08.S5(O3)
Real number (ℝ)

High correlation 

Distinct1744
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean975.07203
Minimum-200
Maximum2523
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-05-21T21:41:38.097024image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile348
Q1700
median942
Q31255
95-th percentile1750
Maximum2523
Range2723
Interquartile range (IQR)555

Descriptive statistics

Standard deviation456.93818
Coefficient of variation (CV)0.46861993
Kurtosis0.63829664
Mean975.07203
Median Absolute Deviation (MAD)272
Skewness-0.03466188
Sum9123749
Variance208792.5
MonotonicityNot monotonic
2025-05-21T21:41:38.378021image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
836 20
 
0.2%
825 20
 
0.2%
826 19
 
0.2%
926 18
 
0.2%
799 17
 
0.2%
777 17
 
0.2%
949 16
 
0.2%
891 16
 
0.2%
923 16
 
0.2%
Other values (1734) 8832
94.4%
ValueCountFrequency (%)
-200 366
3.9%
221 1
 
< 0.1%
225 1
 
< 0.1%
227 1
 
< 0.1%
232 1
 
< 0.1%
252 1
 
< 0.1%
253 1
 
< 0.1%
257 1
 
< 0.1%
261 2
 
< 0.1%
262 1
 
< 0.1%
ValueCountFrequency (%)
2523 1
< 0.1%
2522 1
< 0.1%
2519 1
< 0.1%
2515 1
< 0.1%
2494 1
< 0.1%
2480 1
< 0.1%
2475 1
< 0.1%
2465 1
< 0.1%
2452 1
< 0.1%
2434 1
< 0.1%

T
Real number (ℝ)

High correlation 

Distinct437
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.778305
Minimum-200
Maximum44.6
Zeros1
Zeros (%)< 0.1%
Negative379
Negative (%)4.1%
Memory size73.2 KiB
2025-05-21T21:41:38.698823image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile2.5
Q110.9
median17.2
Q324.1
95-th percentile34.3
Maximum44.6
Range244.6
Interquartile range (IQR)13.2

Descriptive statistics

Standard deviation43.203623
Coefficient of variation (CV)4.4183141
Kurtosis18.774807
Mean9.778305
Median Absolute Deviation (MAD)6.6
Skewness-4.445467
Sum91495.6
Variance1866.553
MonotonicityNot monotonic
2025-05-21T21:41:38.930798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
20.8 57
 
0.6%
21.3 54
 
0.6%
13.8 51
 
0.5%
20.2 51
 
0.5%
12.3 49
 
0.5%
15.6 49
 
0.5%
12 49
 
0.5%
16.3 48
 
0.5%
19.8 48
 
0.5%
Other values (427) 8535
91.2%
ValueCountFrequency (%)
-200 366
3.9%
-1.9 1
 
< 0.1%
-1.4 1
 
< 0.1%
-1.3 2
 
< 0.1%
-1.2 1
 
< 0.1%
-1.1 1
 
< 0.1%
-0.6 2
 
< 0.1%
-0.5 1
 
< 0.1%
-0.3 1
 
< 0.1%
-0.2 1
 
< 0.1%
ValueCountFrequency (%)
44.6 1
 
< 0.1%
44.3 1
 
< 0.1%
43.4 1
 
< 0.1%
43.1 1
 
< 0.1%
42.8 3
< 0.1%
42.7 1
 
< 0.1%
42.6 1
 
< 0.1%
42.5 1
 
< 0.1%
42.2 2
< 0.1%
42 2
< 0.1%

RH
Real number (ℝ)

Distinct754
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.48538
Minimum-200
Maximum88.7
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-05-21T21:41:39.183227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile15
Q134.1
median48.6
Q361.9
95-th percentile77.6
Maximum88.7
Range288.7
Interquartile range (IQR)27.8

Descriptive statistics

Standard deviation51.216145
Coefficient of variation (CV)1.2970914
Kurtosis15.764154
Mean39.48538
Median Absolute Deviation (MAD)13.9
Skewness-3.9324074
Sum369464.7
Variance2623.0935
MonotonicityNot monotonic
2025-05-21T21:41:39.410680image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
53.1 31
 
0.3%
47.8 30
 
0.3%
57.9 30
 
0.3%
60.8 27
 
0.3%
45.9 27
 
0.3%
43.4 26
 
0.3%
50.9 26
 
0.3%
49.8 26
 
0.3%
50.1 26
 
0.3%
Other values (744) 8742
93.4%
ValueCountFrequency (%)
-200 366
3.9%
9.2 2
 
< 0.1%
9.3 1
 
< 0.1%
9.6 1
 
< 0.1%
9.8 1
 
< 0.1%
9.9 2
 
< 0.1%
10 2
 
< 0.1%
10.2 1
 
< 0.1%
10.4 1
 
< 0.1%
10.7 1
 
< 0.1%
ValueCountFrequency (%)
88.7 1
 
< 0.1%
87.2 1
 
< 0.1%
87.1 1
 
< 0.1%
87 1
 
< 0.1%
86.6 2
< 0.1%
86.5 2
< 0.1%
86 1
 
< 0.1%
85.7 3
< 0.1%
85.6 1
 
< 0.1%
85.5 1
 
< 0.1%

AH
Real number (ℝ)

High correlation 

Distinct6684
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-6.8376036
Minimum-200
Maximum2.231
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-05-21T21:41:39.648184image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile0.29506
Q10.6923
median0.9768
Q31.2962
95-th percentile1.72044
Maximum2.231
Range202.231
Interquartile range (IQR)0.6039

Descriptive statistics

Standard deviation38.97667
Coefficient of variation (CV)-5.7003407
Kurtosis20.613092
Mean-6.8376036
Median Absolute Deviation (MAD)0.3022
Skewness-4.7545703
Sum-63979.457
Variance1519.1808
MonotonicityNot monotonic
2025-05-21T21:41:39.866851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
0.7487 6
 
0.1%
0.8394 6
 
0.1%
0.9684 6
 
0.1%
0.9722 6
 
0.1%
1.1199 6
 
0.1%
0.8325 5
 
0.1%
0.8736 5
 
0.1%
0.6686 5
 
0.1%
1.0594 5
 
0.1%
Other values (6674) 8941
95.6%
ValueCountFrequency (%)
-200 366
3.9%
0.1847 1
 
< 0.1%
0.1862 1
 
< 0.1%
0.191 1
 
< 0.1%
0.1975 1
 
< 0.1%
0.1988 1
 
< 0.1%
0.2029 1
 
< 0.1%
0.2031 1
 
< 0.1%
0.2062 1
 
< 0.1%
0.2086 1
 
< 0.1%
ValueCountFrequency (%)
2.231 1
< 0.1%
2.1806 1
< 0.1%
2.1766 1
< 0.1%
2.1719 1
< 0.1%
2.1395 1
< 0.1%
2.1362 1
< 0.1%
2.1247 1
< 0.1%
2.1195 1
< 0.1%
2.117 1
< 0.1%
2.1164 1
< 0.1%

Interactions

2025-05-21T21:41:29.320857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:51.795436image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:53.997077image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:56.234872image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:58.663982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:01.469393image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:04.217539image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:06.769135image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:09.377095image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:14.274299image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:19.562715image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:24.006822image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:26.987122image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:29.480274image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:52.091188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:54.184898image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:56.396885image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:58.858927image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:01.735440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:04.408375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:06.919841image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:09.585752image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:14.635408image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:19.880361image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:24.246823image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:27.177356image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:29.675245image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:52.205586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:54.383927image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:56.581404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:59.049389image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:02.138023image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:04.599628image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:07.087329image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:09.803695image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:14.960745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:20.214604image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:24.513686image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:27.356298image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:29.904852image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:52.377110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:54.535734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:56.794494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:59.279986image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:02.327051image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:04.823303image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:07.312628image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:10.142998image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:15.341787image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:20.605808image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:24.768867image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:27.526973image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:30.087218image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:52.577083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:54.673926image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:57.002491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:59.442263image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:02.521181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:05.029693image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:07.464272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:10.486404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:15.698154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:20.950344image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:24.947040image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:27.723479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:30.296896image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:52.722429image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:54.807049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:57.117466image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:59.637218image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:02.735385image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:05.218384image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:07.622335image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:10.841229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:16.031191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:21.262703image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:25.357081image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:27.891781image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:30.489139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:52.911721image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:54.941778image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:57.248827image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:59.837163image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:02.910171image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:05.402987image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:07.861788image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:11.285588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:16.387492image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:21.646699image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:25.513859image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:28.060536image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:30.677063image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:53.057023image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:55.090104image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:57.455853image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:00.009619image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:03.080532image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:05.652716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:08.040490image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:11.742212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:16.791719image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:22.009954image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:25.720536image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:28.248909image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:30.866971image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:53.201151image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:55.289480image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:57.616991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:00.332253image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:03.256521image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:05.843396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:08.211628image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:12.292832image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:17.223405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:22.339658image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:25.906973image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:28.407025image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:31.033769image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:53.377103image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:55.417714image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:57.884379image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:00.545627image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:03.439889image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:06.016815image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:08.399129image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:12.724786image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:17.772580image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:22.736934image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:26.146866image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:28.603699image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:31.216816image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:53.569988image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:55.607085image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:58.066741image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:00.755703image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:03.627180image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:06.214502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:08.566945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:13.146821image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:18.210190image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:23.045492image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:26.331398image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:28.807063image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:31.397262image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:53.703383image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:55.777071image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:58.216731image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:01.006791image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:03.825702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:06.398730image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:08.740046image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:13.511176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:18.667163image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:23.430878image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:26.558101image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:28.941832image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:31.586792image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:53.887760image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:56.049774image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:40:58.433096image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:01.235245image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:04.030413image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:06.596945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:09.181987image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:13.875939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:19.149412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:23.729759image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:26.767157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2025-05-21T21:41:29.109629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2025-05-21T21:41:40.076897image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
AHC6H6(GT)CO(GT)NMHC(GT)NO2(GT)NOx(GT)PT08.S1(CO)PT08.S2(NMHC)PT08.S3(NOx)PT08.S4(NO2)PT08.S5(O3)RHT
AH1.0000.283-0.114-0.157-0.330-0.2430.2350.283-0.0800.6850.1870.2510.735
C6H6(GT)0.2831.0000.5900.0280.4570.4800.9021.000-0.6420.7770.8880.0040.357
CO(GT)-0.1140.5901.0000.1360.7700.8130.5840.590-0.5800.3050.576-0.043-0.071
NMHC(GT)-0.1570.0280.1361.0000.022-0.0380.1320.0280.1610.1200.0250.011-0.096
NO2(GT)-0.3300.4570.7700.0221.0000.9060.4760.457-0.5220.0610.498-0.134-0.203
NOx(GT)-0.2430.4800.813-0.0380.9061.0000.5070.480-0.5810.0660.5510.058-0.263
PT08.S1(CO)0.2350.9020.5840.1320.4760.5071.0000.902-0.6450.6860.9060.1950.185
PT08.S2(NMHC)0.2831.0000.5900.0280.4570.4800.9021.000-0.6420.7770.8880.0040.357
PT08.S3(NOx)-0.080-0.642-0.5800.161-0.522-0.581-0.645-0.6421.000-0.363-0.6520.0380.008
PT08.S4(NO2)0.6850.7770.3050.1200.0610.0660.6860.777-0.3631.0000.6100.0540.658
PT08.S5(O3)0.1870.8880.5760.0250.4980.5510.9060.888-0.6520.6101.0000.2260.111
RH0.2510.004-0.0430.011-0.1340.0580.1950.0040.0380.0540.2261.000-0.369
T0.7350.357-0.071-0.096-0.203-0.2630.1850.3570.0080.6580.111-0.3691.000

Missing values

2025-05-21T21:41:31.927086image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-21T21:41:32.333258image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

DateTimeCO(GT)PT08.S1(CO)NMHC(GT)C6H6(GT)PT08.S2(NMHC)NOx(GT)PT08.S3(NOx)NO2(GT)PT08.S4(NO2)PT08.S5(O3)TRHAH
03/10/200418:00:002.6136015011.9104616610561131692126813.648.90.7578
13/10/200419:00:002.012921129.4955103117492155997213.347.70.7255
23/10/200420:00:002.21402889.093913111401141555107411.954.00.7502
33/10/200421:00:002.21376809.294817210921221584120311.060.00.7867
43/10/200422:00:001.61272516.583613112051161490111011.259.60.7888
53/10/200423:00:001.21197384.775089133796139394911.259.20.7848
63/11/20040:00:001.21185313.669062146277133373311.356.80.7603
73/11/20041:00:001.01136313.367262145376133373010.760.00.7702
83/11/20042:00:000.91094242.360945157960127662010.759.70.7648
93/11/20043:00:000.61010191.7561-2001705-200123550110.360.20.7517
DateTimeCO(GT)PT08.S1(CO)NMHC(GT)C6H6(GT)PT08.S2(NMHC)NOx(GT)PT08.S3(NOx)NO2(GT)PT08.S4(NO2)PT08.S5(O3)TRHAH
93474/4/20055:00:000.5888-2001.35287710775398757810.459.90.7550
93484/4/20056:00:001.11031-2004.47301827609311299059.563.10.7531
93494/4/20057:00:004.01384-20017.41221594470155160014579.761.90.7446
93504/4/20058:00:005.01446-20022.413625864151741777170513.548.90.7553
93514/4/20059:00:003.91297-20013.611025235071871375158318.236.30.7487
93524/4/200510:00:003.11314-20013.511014725391901374172921.929.30.7568
93534/4/200511:00:002.41163-20011.410273536041791264126924.323.70.7119
93544/4/200512:00:002.41142-20012.410632936031751241109226.918.30.6406
93554/4/200513:00:002.11003-2009.5961235702156104177028.313.50.5139
93564/4/200514:00:002.21071-20011.91047265654168112981628.513.10.5028